Abstrakti
Small and Medium-size Enterprises require increasingly versatile robots that are capable of learning new skills during their operating life span, in addition to the ability to integrate themselves into human teams as a new and effective partner. Teaching information and skills to a robot can quickly become very complex, especially when considering that the human partner of the robot is inexperienced in the field and does not have access to intuitive interaction channels to train such robots. In this work, a system is proposed that can virtually define an assembly task, based on CAD modelling that describe constraints between assembly parts. These constraints are then extracted in an ontology which is automatically translated into Simple Temporal Networks (STNs) leading to joint action plans.Results show the automatic translation between virtual teaching and knowledge acquired by the robot on a peg-in-hole problem before illustrating the connection to planning for human-robot collaborative tasks. As a proof of concept, these developments demonstrate that a CAD guided assembly planner can circumvent the need for skilled robot programming.
Alkuperäiskieli | Englanti |
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Otsikko | Proceedings of the 2020 IEEE International Conference on Human-Machine Systems, ICHMS 2020 |
Toimittajat | Giancarlo Fortino, Fei-Yue Wang, Andreas Nurnberger, David Kaber, Rino Falcone, David Mendonca, Zhiwen Yu, Antonio Guerrieri |
Kustantaja | IEEE |
Sivumäärä | 6 |
ISBN (elektroninen) | 9781728158716 |
ISBN (painettu) | 978-1-7281-5872-3 |
DOI - pysyväislinkit | |
Tila | Julkaistu - syysk. 2020 |
OKM-julkaisutyyppi | A4 Artikkeli konferenssijulkaisussa |
Tapahtuma | IEEE International Conference on Human-Machine Systems - Virtual, Rome, Italia Kesto: 7 syysk. 2020 → 9 syysk. 2020 |
Conference
Conference | IEEE International Conference on Human-Machine Systems |
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Maa/Alue | Italia |
Kaupunki | Virtual, Rome |
Ajanjakso | 7/09/20 → 9/09/20 |
Julkaisufoorumi-taso
- Jufo-taso 1
!!ASJC Scopus subject areas
- Human-Computer Interaction